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Hi,

On 29/06/2015 06:34, CatDog wrote:
> 1. According to the output of clinfo (in the attachment), I have
> two OpenCL platform, in the NV GT 620 GPU platform. clinfo.out
> indicates I have 96 cores and ~256MB RAM. But in the output of
> nvidia-smi (in the following lines), I have 1024MB RAM. Is it a
> feature or a bug? The same phenomena occurs in CPU platform,
> clinfo.out indicates I have 64 cores and ~63GB RAM, but actually I
> have 256GB RAM.

OpenCL limits the size of any one single allocation to 1/4 of the
total memory of the device.  Some OpenCL implementations have
environmental variables which allow a single allocation to go above
this.  This should not be an issue for PyFR which performs multiple
allocations none of which should be greater than 1/4 of the device memor
y.

> The result indicates the program is not so clever to use OpenMP on
> each NUMA. right? How to improve this? The opencl related env.
> vars. related to this problem is GOMP_CPU_AFFINITY. Is it possible
> to use it to bind openmp on one NUMA?

As I indicated in my previous e-mail this is known to be a pain.  With
Intel MPI and ICC everything should 'just work'.  More recent versions
of OpenMPI (1.8 and later) also make this relatively painless.  In
these scenarios it is important to use a single threaded BLAS library
and to let PyFR handle the parallelism with OpenMP.  Otherwise
everything becomes twice as complicated.

Regards, Freddie.

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